针对岩土热响应试验数据处理中的不确定性问题,开发了柱热源传热模型数值反演解与信赖域反射优化算法相结合的地下岩土热物性参数估计程序.该程序能够有效地避免求解过程陷入局部最优解,并为后续不确定性研究提供底层模型.对地埋管进出水温度、热传输功率、地下原始温度等模型输入参数的不确定性通过查阅文献、理论思考和基于专业经验的假设进行合理量化,采用Monte Carlo方法进行模拟,将热响应试验的模型输入参数不确定性传播到输出参数评估结果中,得到了地下岩土导热系数与钻孔热阻之间的二元联合分布,并使用Copula函数进行复现.最后对传热模型中影响温度输出的可变参数进行Lasso敏感性分析,证明导热系数与热阻的影响最大.In order to solve the uncertainty in data interpretation involved in soil-rock thermal response test(TRT), a parameter estimation program was developed by employing numerical inversion of cylindrical source model combined with a trust region reflective algorithm, which can avoid being trapped in local optimum and provide underlying model for subsequent uncertainty study.Uncertainties of input parameters, including inlet and outlet temperatures of ground heat exchanger, heat transfer rate and undisturbed ground temperature, etc, were reasonably quantified through literature reviews, theoretical considerations and educated guesses.Then, Monte Carlo stochastic simulation was applied to propagate input parameters uncertainties to output parameters of TRT.A mapping of ground thermal conductivity and borehole thermal resistance was then obtained, and their inherent correlation was presented by a bivariate joint distribution constructed by Copula function.In the end, the influence of variable parameters on the mean temperature of heat transfer fluid was analyzed by Lasso method.The result shows that ground thermal conductivity and borehole thermal resistance are the most influential parameters.

SCOPUSTM Citations

Page view(s)

Google ScholarTM

Altmetric

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

The Library actively supports the
University’s mission by providing integrated and timely access to high
quality scholarly resources, an inspiring environment for intellectual
growth and discovery, with responsive and outreaching services...
[read more ]